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1) They're unlikely to be sentient (few neurons, immobile)
2) If they are sentient, the farming practices look likely to be pretty humane
3) They're extremely nutritionally dense
Buying canned smoked oysters/mussels and eating them plain or on crackers is super easy and cheap.
It's an acquired taste for some, but I love them.
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Learning from Inspiring Figures in Our Community
Background
This post emerged from discussions during the EA values project, where we observed that many community members cite specific individuals (whether EA founders, organization leaders, or mentors) as key influences in their journey into effective altruism. Understanding who inspires us and why can help us identify the values and approaches that make EA compelling to newcomers and sustaining for existing members.
Historical movements have often been shaped by individuals who embodied their core principles in compelling ways. From Gandhi's commitment to nonviolence to scientists like Marie Curie who persevered despite systemic barriers, these figures serve not just as leaders but as concrete examples of abstract values in action.
The Value of Role Models in EA
Role models serve several important functions:
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Outline:
(00:10) Learning from Inspiring Figures in Our Community
(00:15) Background
(01:00) The Value of Role Models in EA
(01:46) Categories for Discussion
(02:42) Some Starting Examples
(03:30) Guidelines for discussions and comments
(04:02) The hope moving forward
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This is a lightly-edited memo I wrote for the 2025 Animal Advocacy Strategy Forum, which were encouraged to be highly opinionated to generate strategy discussion.
It seems strange to me that animal advocates rely on animal ag to come up with the solutions that we want to see. We identify a problem, we look to see what exists in the world, we try to find the best of those things, and then we try to get them implemented.
I would like to see welfare-oriented engineers actively develop the tech that we want to see deployed on farms.
For example, Shrimp Welfare Project is trying to get new stunners developed, which I'm excited about [1]. But I think there are a lot of other examples that this would work for. In-Ovo sexing seems like another good example of technology that I'm kind of surprised that the animal movement wasn't more [...]
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Climate change doesn't rank as a top EA cause area because it already receives substantial funding, is less neglected than other risks, and—under gradual-warming scenarios—seems unlikely to cause human extinction. I broadly agree with that assessment.
Yet some problems under the climate umbrella do fit EA criteria of scale, neglectedness, and tractability. Climate tipping points in particular could trigger catastrophic feedback loops—mass human suffering, great-power conflict, biodiversity collapse, and wild-animal suffering—while still attracting little targeted funding.
Conversations with long-time climate experts reinforce that most money still flows to mitigation; far less supports adaptation or contingency planning. From a “maximizing impact at the margins” perspective, work that limits damage once a tipping point is crossed looks unusually cost-effective, even if it is unfashionable in some environmental circles (it can feel like “admitting defeat”). Preparedness and response planning could therefore make a decisive difference. I would welcome the community's perspective [...]
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Outline:
(02:27) Assessing the Risk of Global Catastrophic Food Failure from AMOC Collapse
(03:53) Introduction
(04:27) Overview of the Atlantic Meridional Overturning Circulation (AMOC)
(07:05) AMOC Weakening and Tipping Potential
(12:59) Impacts
(18:53) Timelines and Early Warnings
(22:15) Recommendations for Resilience and Further Research
(24:03) References
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If you are planning on doing AI policy communications to DC policymakers, I recommend watching the full video of the Select Committee on the CCP hearing from this week.
In his introductory comments, Ranking Member Representative Krishnamoorthi played a clip of Neo fighting an army of Agent Smiths, described it as misaligned AGI fighting humanity, and then announced he was working on a bill called "The AGI Safety Act" which would require AI to be aligned to human values.
On the Republican side, Congressman Moran articulated the risks of AI automated R&D, and how dangerous it would be to let China achieve this capability.
Additionally, 250 policymakers (half Republican, half Democrat) signed a letter saying they don't want the Federal government to ban state level AI regulation.
The Overton window is rapidly shifting in DC, and I think people should re-evaluate what the [...]
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In response to Matthew's post about the objectivity of morality, I'd thought I'd throw out a(n initially -- this became much longer than I was expecting) short post explaining why I think this view is pretty implausible.
I have another post on my Substack that shows why I think some other arguments for moral realism fail (though I'm not sure I endorse everything I argue there anymore...). If you like this one, check it out!
Note: The formatting of this article got a little messed up (inconsistent about ordering with the numbered and lettered bullets, etc), but it should still be understandable and fairly readable. Also, I didn't spend much time editing because I wanted to get this out so apologies in advance.
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An objection against trying to reduce suffering is that we cannot predict whether our actions will reduce or increase suffering in the long term. Relatedly, some have argued that we are clueless about the effects that any realistic action would have on total welfare, and this cluelessness, it has been claimed, undermines our reason to help others in effective ways. For example, DiGiovanni (2025) writes: “if my arguments [about cluelessness] hold up, our reason to work on EA causes is undermined.”
There is a grain of truth in these claims: we face enormous uncertainty when trying to reduce suffering on a large scale. Of course, whether we are bound to be completely clueless about the net effects of any action is a much stronger and more controversial claim (and one that I am not convinced of). Yet my goal here is not to discuss the [...]
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Outline:
(01:50) A potential approach: Giving weight to scope-adjusted views
(04:40) Asymmetry in practical recommendations
(05:40) Toy models
(08:25) Justifications and motivations
(08:50) Why give weight to multiple views?
(10:47) Why give weight to a scope-adjusted view?
(17:30) Arguments I have not made
(19:12) Conclusion
(20:01) Acknowledgments
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Linkpost URL:
https://magnusvinding.com/2025/06/25/reducing-suffering-given-long-term-cluelessness/
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Summary
To quickly transform the world, it's not enough for AI to become super smart (the "intelligence explosion").
AI will also have to turbocharge the physical world (the "industrial explosion"). Think robot factories building more and better robot factories, which build more and better robot factories, and so on.
The dynamics of the industrial explosion has gotten remarkably little attention.
This post lays out how the industrial explosion could play out, and how quickly it might happen.
We think the industrial explosion will unfold in three stages:
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Outline:
(00:11) Summary
(01:44) Intro
(04:18) The industrial explosion will start after the intelligence explosion, and will proceed more slowly
(06:53) Three stages of industrial explosion
(07:41) AI-directed human labour
(09:23) Fully autonomous robot factories
(12:07) Nanotechnology
(13:04) How fast could an industrial explosion be?
(13:39) Initial speed
(16:19) Acceleration
(17:36) Maximum speed
(19:59) Appendices
(20:02) How fast could robot doubling times be initially?
(27:45) How fast could robot doubling times accelerate?
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Linkpost URL:
https://www.forethought.org/research/the-industrial-explosion
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Summary
To quickly transform the world, it's not enough for AI to become super smart (the "intelligence explosion").
AI will also have to turbocharge the physical world (the "industrial explosion"). Think robot factories building more and better robot factories, which build more and better robot factories, and so on.
The dynamics of the industrial explosion has gotten remarkably little attention.
This post lays out how the industrial explosion could play out, and how quickly it might happen.
We think the industrial explosion will unfold in three stages:
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Outline:
(00:13) Summary
(01:46) Intro
(04:34) The industrial explosion will start after the intelligence explosion, and will proceed more slowly
(06:56) Three stages of industrial explosion
(08:00) AI-directed human labour
(09:42) Fully autonomous robot factories
(12:26) Nanotechnology
(13:23) How fast could an industrial explosion be?
(13:58) Initial speed
(16:37) Acceleration
(17:55) Maximum speed
(20:17) Appendices
(20:21) How fast could robot doubling times be initially?
(28:03) How fast could robot doubling times accelerate?
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First published:
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Linkpost URL:
https://www.forethought.org/research/the-industrial-explosion
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Many thanks to Max Taylor, Alistair Stewart, Albert Didriksen, Jeff and Johannes Pichler for feedback on this post. All mistakes are my own. This post does not necessarily reflect the views of my employer.
Executive Summary---
Outline:
(00:24) Executive Summary
(02:07) Introduction
(04:00) Influence and Values
(06:00) Interest and Alternatives
(09:06) Symmetries and Asymmetries
(09:47) Conclusion
The original text contained 2 footnotes which were omitted from this narration.
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